Genomic Variation

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.title[
# Genomic Variation
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.author[
### Ratnesh Bhai Mehta • 28-Apr-2023
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.institute[
### Zifo RnD Solutions
]

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## Topics covered

* What is genetic variation?

* Types of genetic variation studies

* Variant identification and analysis

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## Genetic variation

### Germline vs Somatic Variants

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## Genetic variation

### What makes us unique?

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## Genetic variation

### Types of variation

* **RFLP: Restriction Fragment Length Polymorphism**

* **VNTR: Variable Number of Tandem Repeats**
    * or minisatellite
    * ~10-100 bp core unit

* **SSR : Simple Sequence Repeat** 
    * or STR (simple tandem repeat) 
    * or microsatellite
    * ~1-5 bp core unit
  
* **SNP: Single Nucleotide Polymorphism**
  * Commonly used to also include rare variants (SNVs)
  
* **Insertions or deletions**
  * INDEL – small (few nucleotides) insertion or deletion

* **Rearrangement** (inversion, duplication, complex rearrangement)
  * CNV: **C**opy **N**umber **V**ariation

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## Genetic variation

### Single Nucleotide Polymorphishm and Mutation

* **Genetic Polymorphism**
 * Common variation in the population:
 * Phenotype (eye color, height, etc.)
 * Genotype (DNA sequence polymorphism)
 * Frequency of minor allele(s) >= 1%
* **DNA sequence variation**
 * Most common <= 0.99 (Polymorphism)
 * Minor allele >= 1%
 * Rare variant < 0.01%
* **DNA mutation – any change in DNA sequence**
 * Silent vs. amino acid substitution vs. other
 * Neutral vs. disease-causing
 * 1X10-8/bp/generation (~70 new mutations/individual)
* **Common but incorrect usage**
 * “Mutation” vs. ”Polymorphism”

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## Genetic variation

### Mutation

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* A mutation is a change in the “normal” base pair sequence.

* Can be:
 * A single base pair substitution
 * A deletion or insertions of 1 or more base pairs (indel)
 * A larger deletion/insertion or rearrangement

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## Genetic variaion

### Silent Sequence Change (Synonymous SNP)

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##  Genetic variaion

### Missense Mutation (Non-Synonymous SNP)

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## Genetic variaion

### Nonsense Mutation (Non-Synonymous SNP)

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## Genetic variation

### Frameshift Mutation (Non-Synonymous SNP)

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## Genetic variation

### Splice Site Mutation

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## Genetic variation

### Other Variant Types

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## Genetic variation

### Size Spectrum of Human Sequence Variation

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## Genetic Variation Studies

### Genome Wide Association Studies (GWAS)

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* Genotyping individuals at common variants across
  the genome using genome wide SNP arrays.
  
* Variants associated with trait, or within the
  same haplotype as a variant associated with a
  trait, will be found at a higher frequency in cases
  than controls.
  
* Statistical analysis is carried out to indicate how
  likely a variant is to be associated with a trait.
  The p-value of the association indicates how likely
  the variant is to be associated with the trait.
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## Genetic Variation Studies

### Functional Genetic Variation Studies

* **Aim:** understand the molecular mechanisms and pathways that link genotype to
  phenotype.
  
* Simple variants that alter the translated protein sequence, such as, missense, splice   site variant, stop gained, stop lost variants, can cause functional consequences by:

* Altering ligand and/or co-factor binding sites
 * Alter the natural protein structure by:
   * Removing or adding additional cysteine reduces that can alter disulfide bond 
     patterns
   * Alter normal formation of secondary structure elements or their interaction
     (sickle cell anemia is an example of this)
   * Disrupt the normal interactions between proteins’ tertiary protein complexes or
     other cellular components
 * Remove or add post-translational modification sites.
 
* Personalize medicine, precision medicine, ACMG guidelines

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## Genetic Variation Studies

### Population Genetics

* Study of variation within populations of individuals.
* Data from genome-scale population genetics studies has been used to:

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## Variant Identification and Analysis

### Technologies

* **SNP Array**

* **Next Generation Sequencing**
   * Gene Panel Sequencing 
   * Whole Exome Sequencing (WES)
   * Whole Genome Sequencing (WGS)
   
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## Variant Identification and Analysis

### Microarray

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* **Microscopic slide usually made of glass, silicon chip or nylon membrane.**

* **Surface provided with thousands of minute pores in defined positions**.

* **Able researchers analyze thousands of genes in a single reaction.**

* **Various types:**
   * DNA microarrays, MMChips, Protein microarrays,
     Peptide microarrays, Tissue microarrays, Cellular
     microarrays, Chemical compound microarrays,
     Antibody microarrays, Carbohydrate microarrays,
     Phenotype microarrays, Reverse phase protein
     microarrays, Interferometric reflectance imaging
     sensor or IRIS.
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## Variant Identification and Analysis

### DNA microarray

* **Types:** cDNA microarrays, oligo DNA microarrays, BAC microarrays and SNP microarrays.

* SNP microarray **works on the principle of DNA hybridization in which a single base change can be detected through fluorescence chemistry.**

* Application:
   * Haplotype and gene mapping
   * Cancer research
   * Personalized genetic research
   * Genetic medicine research
   * Genome-wide association studies
* SNP array completes in three common steps:
   * Immobilization oligonucleotides/probes (make a chip)
   * Fragmentation and labelling nucleic acid
   * Hybridization
   
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## Variant Identification and Analysis

### Major Techniques for Detection of SNPs Using Microarrays

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## Variant Identification and Analysis

### SNP Array Process Flow

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## Variant Identification and Analysis

### Raw Intensity File to VCF (Illumina)

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## Variant Identification and Analysis

### Raw Intensity File to VCF (Illumina & Affymetrix)

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## Variant Identification and Analysis

### Next Generation Sequencing (NGS)

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## Variant Identification and Analysis

### Framework for Variant Discovery (NGS)

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## Variant Identification and Analysis

### Mapping (NGS)

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* **Place reads with an initial alignment on the reference genome using 
  mapping algorithms.
* Refine initial alignments
   * local realignment around indels
   * molecular duplicates are eliminated
* Generate the technology-independent SAM/BAM alignment map 
  format.
  
    **Accurate mapping crucial for variation discovery**
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## Variant Identification and Analysis

### Discovery of Raw Variants

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* Analysis-ready SAM/BAM files are analyzed to 
  discover all sites with statistical evidence for 
  an alternate allele present among the 
  samples.
* SNPs, SNVs, short indels, and SVs.
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## Variant Identification and Analysis

### Discovery of Analysis Ready Variants

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* Technical covariates, known sites of variation,
  genotypes for individuals, linkage
  disequilibrium, and family and population
  structure are integrated with the raw variant
  calls from Phase 2 to separate true
  polymorphic sites from machine artifacts.
* At these sites high-quality genotypes are 
  determined for all samples.
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## Variant Identification and Analysis

### Variant Call Format (VCF)

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## Variant Identification and Analysis

### Header Line

* The header line names the 8 fixed, mandatory columns;

* If genotype data is present in the file, these are followed by a FORMAT column header,
then an arbitrary number of sample IDs.

* The header line is tab-delimited.

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## Variant Identification and Analysis

### Array vs NGS

<table>
 <thead>
 <tr>
 <th style="text-align:left;"> ARRAY </th>
 <th style="text-align:left;"> ARRAY.1 </th>
 <th style="text-align:left;"> NGS </th>
 <th style="text-align:left;"> NGS.1 </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:left;"> Pros </td>
 <td style="text-align:left;"> Cons </td>
 <td style="text-align:left;"> Pros </td>
 <td style="text-align:left;"> Cons </td>
 </tr>
 <tr>
 <td style="text-align:left;"> Relatively Inexpensive </td>
 <td style="text-align:left;"> High background, low sensitivity </td>
 <td style="text-align:left;"> Low background, very sensitive </td>
 <td style="text-align:left;"> Expensive </td>
 </tr>
 <tr>
 <td style="text-align:left;"> Easy Sample Prep </td>
 <td style="text-align:left;"> Limited dynamic range </td>
 <td style="text-align:left;"> Large dynamic range </td>
 <td style="text-align:left;"> Complex sample preparation </td>
 </tr>
 <tr>
 <td style="text-align:left;"> Mature informatics &amp; Stats. </td>
 <td style="text-align:left;"> Not quantitative </td>
 <td style="text-align:left;"> Quantitative </td>
 <td style="text-align:left;"> Limited bioinformatics </td>
 </tr>
 <tr>
 <td style="text-align:left;"> </td>
 <td style="text-align:left;"> Competitive hybridization </td>
 <td style="text-align:left;"> </td>
 <td style="text-align:left;"> Massive information technology infrastructure required </td>
 </tr>
 <tr>
 <td style="text-align:left;"> </td>
 <td style="text-align:left;"> Annotation probes </td>
 <td style="text-align:left;"> </td>
 <td style="text-align:left;"> </td>
 </tr>
</tbody>
</table>
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## Variant Identification and Analysis

### Tasks (NGS)

* Article reading and discuss

* [DePristo, M.A. et al. A framework for variation discovery and genotyping using 
     next-generation DNA sequencing data. Nat Genet. 43(5):491-8. PMID: 21478889 
     (2011).](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3083463/)
     
   * [Narendra M. et al. A Bioinformatics Pipeline for Whole Exome Sequencing: 
     Overview of the Processing and Steps from Raw Data to Downstream Analysis 
     .BioRxiv (2017).](https://www.biorxiv.org/content/10.1101/201145v1.full)
     
* Hands on “Disease causing mutation” (NGS)

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### Terminologies

* **Variation:** any difference between individuals of a particular species.

* **Mutation:** alteration in the nucleotide sequence of a gene.

* **Alleles:** Different versions of the same variant.

* **Reference allele:** to the base that is found in the reference genome.

* **Alternative allele:** any base, other than the reference allele found at that locus
    (position).
    
* **Major allele:** most common allele for a given SNP.

* **Minor allele:** less common allele for a given SNP. MAF (Minor Allele Frequency)

* **Genotype:** genetic make-up of an individual.

* **Phenotype:** physical traits and characteristics of an individual and are influenced     by their genotype and the environment

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# Thank you. Questions?

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Graphics from <img src="./assets/freepik.jpg" style="max-height:20px; vertical-align:middle;"> 
Created: 28-Apr-2023 • James Ashmore • <a href="https://www.zifornd.com/category/omics-bioinformatics">Bioinformatics</a> • <a href="https://www.zifornd.com">Zifo</a>

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